Here is how enterprises will use customer data in 2017

Artificial intelligence and machine learning will soon be used by enterprises to better understand their customers.

Shares

It is no longer enough for businesses to have a dedicated mobile website -- in fact, Gartner predicts that 20 percent of brands will abandon their websites by 2019. Realizing this trend, some companies have already adopted a “mobile first” approach. Separate versions of a site are unwieldy and introduce unnecessary confusion, both when a visitor accesses a site via a different device, or when an IT department attempts to fix a bug on the back end. While individuals still advocate for a central company website, the growing importance of social media cannot be denied.

In a similar way that customers expect a consistent experience across multiple channels and devices, it only makes sense that advanced enterprise digital analytics solutions, such as session replay, click maps, and conversion optimization solutions will converge as well and be supported by web and mobile unified platforms. This convergence of analytics will enable companies to move away from a siloed channel-centric approach and embrace a truly customer centric approach. With 2017 being the tipping point for this shift, below are four predictions that will revolutionize the way enterprises look at customer data:

Complete and automatic recording of digital customer journeys

Contact centers have always recorded telephone calls for training and compliance purposes. More recently, though, many have introduced analytics to gain insight into online experiences, needs, wants and expectations of customers as well. From this data, digital teams and marketers are beginning to understand the benefits of adopting this same approach across their digital channels. This technology is making it possible to automatically record and index 100% of digital customer journeys without any tagging or pre-configuration, even if the website or mobile app undergoes changes. For marketing and analytics executives, this in turn means that they can:

View online customer journeys in real time: With these insights, digital teams and marketers can automatically map trends. From a micro level, these single sessions create a direct connection with individual consumers, providing a deeper level of connectedness. The ability to easily select journey points of interest with automatic filters and funnel this data helps support higher-level investigations more efficiently. An example of this is judging campaign success. Does Campaign A convert more sales for Product A? Or does Campaign B convert on Product B and vice versa?

Optimize forms: The use of click maps can help determine where customers are spending the most time on specific forms. Specifically, which fields are being left bank, when they are being changed, as well as why customers are dropping off. This way companies can better understand why individual customers are leaving survey questions or form fields blank among other things.

Improve conversions and generate new revenues: By viewing customer struggles via visual replay, new revenue streams can also be created using unforeseen knowledge. For retailers, adding a related/popular products section at checkout or more specific product specs could boost conversions long term.

Speed up time-to-insight and time-to-value: By breaking dependency on tag-management solutions or IT, events can be analyzed retroactively as opposed to incrementally. Online businesses can understand for how long an issue has been impacting their visitors or who are the customers that have been struggling due to a specific problem and take remedial actions. Furthermore, by easily exporting identified issues and data for faster resolutions, insights can be shared with IT departments removing the need to reproduce unreproducible errors.

Business analytics will no longer be a siloed solution

Traditionally, analytics have been a way to break down silos and uncover insights. However, these initiatives have been in isolation with IT, customer service, marketing and compliance all running their own analytics systems. Because there is a greater need for transparency between different departments, organizations are moving away from this approach. In its place, a more holistic way of viewing digital operations and customer experience data. Digital analytic solutions will evolve from point solutions to enterprise-wide solutions, supporting a wide range of use cases and business needs, from marketing to compliance, online fraud via customer support, and IT performance monitoring. Access to easily digestible data will be democratized as analytic solutions become more friendly to business owners.

A drive towards compliance ahead of new regulations

Looking ahead, there are several pieces of major regulation coming into force next year, with the Markets in Financial Instruments Directive II (MiFID II) and the Markets in Financial Instruments Regulations (MiFIR) in January and the EU General Data Protection Regulation (GDPR) in May. The next several months will be a frantic time for organizations who will be forced to pick up the pace in order to ensure they have the right systems and processes in place to avoid substantial fines. During this time, record keeping, data protection, monitoring and reporting requirements will all need to be addressed by digital analytics solutions, which will also need to be designed “with compliance in mind” and meet the highest security and privacy standards.

We’re taking step toward machine learning and automatic insights

As enterprises are becoming better at understanding online customer behaviors and what drives them, they will inevitably move to the next plateau, which includes the use of artificial intelligence and machine learning. Analyzing the massive quantity of data generated by today’s digital businesses along with business intelligence and traditional web analytics tools takes time and expertise. Using machine learning algorithms will enable enterprises to isolate issues in real time, support agile processes and rapid business decisions through automatically uncovered insights.

Armed with a host of solutions for tracking data, organizations will be tasked with distilling this information to best serve their customers. More so, these insights must be applied to different channels in order to promote a unified experience. This way, changes to one medium will not cause a negative ripple effect to the others. The main takeaway: companies must utilize and optimize data to drive traffic across all mediums, where a controlled and centralized experience awaits to convert customers.